Classification of Music Moods Based on CNN
Fika Ulfa Widowati, Fitriyanto Santi Nugroho, Guruh Fajar Shidik · 2018 International Seminar on Application for Technology of Information and Communication · 2018
In recent years, music has become part of everyone life. Almost everyone with different backgrounds listening to music, as a form of entertainment or just accompany in doing the activity. Music can be enjoyed in various ways based on the level of society. Usually music is categorized by genre, which shows the type of music or the form of music. Like pop, rock, metal, ballad, dangdut, jazz, keroncong, and etc. But the division by genre is common. So, in this study we try to classify a music into some moods like happy, peaceful, angry, and sad. Because such a classification will be easily accepted by listeners, especially people who are not very familiar with the genre. This classification is performed with 200 track databases for the training data and 50 track database for testing. We use a music features, such as pitch, pulse clarity, tempo, key, and scale. For the classification method in this paper we used Convolutional Neural Networks (CNN), the accuracy that we have are 82%.